Blink AI and EvenFlow AI Partner to Transform Auto Dealership Service Appointment Scheduling
AI-powered partnership connects customer demand with real-time shop capacity to drive higher service revenue and improve customer experience
NORTHFIELD, IL, UNITED STATES, February 3, 2026 /EINPresswire.com/ -- — EvenFlow AI, the industry leader in automotive dealership capacity management, shop loading, and profit optimization announced today a strategic partnership with Blink AI Automotive, the leading AI-powered customer engagement and demand orchestration platform for automotive dealerships.
Announced ahead of National Automobile Dealers Association (NADA) 2026, the partnership delivers a tightly integrated solution that connects customer intent and inbound demand with real-time technician availability and operational constraints by service mix, enabling dealers to more intelligently schedule appointments that maximize Fixed Ops revenue without hiring more technicians.
For the first time, dealers can orchestrate the entire service journey end to end: from inbound calls, digital scheduling, and telematics-driven alerts handled by Blink AI, through to optimized appointment placement and shop utilization powered by EvenFlow AI’s advanced capacity intelligence.
“Dealers don’t have a demand problem — they have a coordination problem,” said Dave Perry, CEO of Blink AI. “Blink AI captures and activates customer demand. EvenFlow AI understands what the shop can actually handle. Together, we close the loop between intent and execution — which is where real Fixed Ops performance is won or lost.”
Solving One of Fixed Ops’ Most Expensive Gaps
Dealerships today face record inbound demand—calls, digital requests, OEM alerts—while service departments struggle with overloaded advisors, uneven shop utilization, and missed revenue opportunities. Traditional schedulers operate in isolation, unaware of real shop constraints, leading to overbooking, underutilization, and poor customer experiences.
The Blink AI + EvenFlow AI partnership directly addresses this gap by:
• Aligning appointment scheduling with true shop capacity
• Balancing the flow of customer demand with technician workloads
• Reducing bottlenecks, “spoiled” technician hours, and appointment fallout
• Increasing repair order throughput while better delivering on customer promise times
“We enable dealers to schedule appointments at the right time with the right resource to drive Fixed Ops profitability”, said Dave Anderson, CEO of EvenFlow AI. “By integrating with Blink AI, dealers can act on demand intelligently and end the days of ‘controlled chaos’ in the service drive.
About EvenFlow AI
EvenFlow AI is a leading provider of AI-powered capacity management and revenue optimization solutions designed for automotive dealership service departments. The company's innovative platform leverages data-driven algorithms to optimize service scheduling, increase lane utilization, and enhance customer satisfaction, all of which contribute to maximizing profitability for dealership partners. For more information, visit www.evenflow.ai
About Blink AI Automotive
Blink AI Automotive is an AI-powered customer engagement and demand orchestration platform built for automotive dealership Fixed Operations. Blink AI captures inbound calls, digital requests, and OEM telematics alerts and turns them into coordinated actions that book appointments, improve service throughput, and drive measurable Fixed Ops revenue—without adding headcount. Serving dealer groups and OEM partners across North America, Blink AI helps dealers turn customer intent into real outcomes. For more information, visit www.blinkai.com
David Anderson
EvenFlow AI
+1 312-241-8536
davea@evenflow.ai
Visit us on social media:
LinkedIn
Legal Disclaimer:
EIN Presswire provides this news content "as is" without warranty of any kind. We do not accept any responsibility or liability for the accuracy, content, images, videos, licenses, completeness, legality, or reliability of the information contained in this article. If you have any complaints or copyright issues related to this article, kindly contact the author above.
